1. Field of the Invention
The present invention relates to a system, a detecting method and a program. Specifically, the present invention relates to a system for analyzing history information of a transaction, a detecting method and a program.
2. Background Art
A data mining for extracting useful information from large quantity of stored data has been studied. With the data mining, a correlation rule of “Consumers buy beer and paper diapers together on Thursday”, for example, based on data of receipts issued from retailers. Accordingly, it is expected for a company to appropriately set its inventory control strategy or its marketing strategy with the data mining without depending on experience or intuition of its manager or its person in charge.
A technique for detecting a set of items (for example, goods) frequently appearing in target data is called frequent pattern mining, which has been studied from various aspects (see R. Agrawal, R. Srikant: Fast Algorithms for Mining Association Rules, Proc. of the 20th Int'l Conference on Very Large Databases, Santiago, Chile, September 1994. Expanded version available as IBM Research Report RJ9839, June 1994). It is also known that it is enough to obtain only a pattern to meet the maximum condition, which is described by using frequency of appearance and an inclusive relation of sets, in order to list all the frequency patterns (see N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal: Discovering frequent closed itemsets for association rules, In 7th Intl. Conf on Database Theory, January 1999). That pattern is called a closed pattern.
It is also known that a frequency pattern can be obtained if only a frequently appeared closed pattern can be obtained and the subsets of the closed pattern are listed (see N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal: Discovering frequent closed itemsets for association rules, In 7th Intl. Conf on Database Theory, January 1999, above). Accordingly, various methods for efficiently obtaining a closed pattern have been studied (for example, see T. Uno, T. Asai, Y. Uchida, H. Arimura: LCM: An Efficient Algorithm for Enumerating Frequent Closed Sets of Items, Proceedings of the ICDM 2003 Workshop on Frequent Itemset Mining Implementations, 2003).
A problem to be solved by the invention will be described by an example in which each sales processing in a certain sales system is considered as a transaction and goods sold together by the sales processing is considered as an item. In this example, database records histories of numeral transactions as sets of items sold in each transaction. A group of goods frequently sold in the sales system can be obtained by obtaining a closed pattern from the database.
In order to effectively use the data mining for a sales strategy, it may not be enough to simply obtain a frequency pattern for all the goods. It may be desired to obtain a frequency pattern only for particular goods which do not sell well for the purpose of investigating the cause of the poor sale. It may also be desired to obtain a frequency pattern only for a group of goods displayed on the same show case for the purpose of reviewing arrangement of goods at a retailer. In such cases, a closed pattern only needs to be detected for an itemspace formed by sets of the particular items.
Displaying ways, sales or the other status of goods depend on passage of time, the place of the shop or the like. Therefore, if a closed pattern is detected for a first itemspace, another closed pattern may need to be obtained for a second itemspace which is the first itemspace added with a new item. In such a case, information on a closed pattern obtained for the first itemspace has been abandoned and a closed pattern for the second itemspace has been newly obtained. For such a reason, a long time is required for detecting a closed pattern even for a small change of the itemspace.
The present invention intends to provide a system for solving the problem mentioned above, a detecting method and a program. The intention is achieved by a combination of features described in independent claims of the claims. Dependent claims thereto define further advantageous specific examples of the present invention.